A on Spam Filtering Classification: A Majority Voting like Approach

Youngsu Dong, Mourad Oussalah, Lauri Lovén

2017

Abstract

Despite the improvement in filtering tools and informatics security, spam still cause substantial damage to public and private organizations. In this paper, we present a majority-voting based approach in order to identify spam messages. A new methodology for building majority voting classifier is presented and tested. The results using SpamAssassin dataset indicates non-negligible improvement over state of art, which paves the way for further development and applications.

Paper Citation

in Harvard Style

Dong Y., Oussalah M. and Lovén L. (2017). A on Spam Filtering Classification: A Majority Voting like Approach.In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, ISBN 978-989-758-271-4, pages 293-301. DOI: 10.5220/0006581102930301

in Bibtex Style

@conference{kdir17,
author={Youngsu Dong and Mourad Oussalah and Lauri Lovén},
title={A on Spam Filtering Classification: A Majority Voting like Approach},
booktitle={Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR,},
year={2017},
pages={293-301},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006581102930301},
isbn={978-989-758-271-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR,
TI - A on Spam Filtering Classification: A Majority Voting like Approach
SN - 978-989-758-271-4
AU - Dong Y.
AU - Oussalah M.
AU - Lovén L.
PY - 2017
SP - 293
EP - 301
DO - 10.5220/0006581102930301